My long-term goal is to become an independent scientific leader in the genetic epidemiology of cancer. My background includes an MD, a PhD in epidemiology, and post- doctoral training in statistical genetics. My immediate career goals are to obtain the necessary training in computational genomics and bioinformatics that would allow me to expand my methodological focus to encompass the integrative analysis of multiple types of genomic data to enhance the detection of cancer-associated genes. The application of these methods to two distinct diseases will considerably broaden my training as a cancer genetic epidemiologist. To this end, I have chosen highly qualified and experienced mentors: Drs. Alice Whittemore (cancer genetic epidemiology), Robert Tibshirani (statistical analysis of genomic data), James Brooks (cancer genomics), and Patrick Brown (genomic analysis of cancer); and developed a training plan that includes coursework in computational genomics and bioinformatics. The overall goal of this proposal is to better understand the genetic bases of ovarian and prostate cancer. The specific aims are to: (1) identify genetic risk factors for ovarian cancer by re-sequencing one of the most promising regions implicated by genome-wide association studies in order to help find the most likely causal variants; (2) identify genetic risk factors for prostate cancer by mining genome-wide association studies and expression data repositories; and (3) define genomic signatures of aggressive prostate tumors based upon a new method for the combined analysis of genome-wide expression level, copy number, and genotype data. The elucidation of the genetic underpinnings of ovarian and prostate cancer may ultimately lead to improvements in risk stratification and prognostication, and better management of these important diseases. The proposed methodology is also applicable to other cancers with available genomic data. This multidisciplinary research and training will form an invaluable experience that will become increasingly important in cancer research as '-omics' technology rapidly advances.